MERCHANTABLE TIMBER PRODUCTION IN DALBERGIA SISSOO PLANTATIONS ACROSS BANGLADESH: REGIONAL PATTERNS, MANAGEMENT PRACTICES AND EDAPHIC FACTORS
Bibliographic record
Abstract
is an extensively planted tree species in Bangladesh, primarily because of its fast growth rate and multiple economic benefits. However, only a few studies have quantified baseline timber volumes attainable under sissoo cultivation in Bangladesh, and even fewer since large-scale sissoo dieback occurred in the mid- and late 1990s. Using data from 72 plantations across five Bangladeshi regions, we derived region-specific rotation-age volume estimates for sissoo. We also examined how sissoo volumes were correlated with plantation characteristics (plantation age, per cent mortality, per cent sissoo and tree density) and soil characteristics (texture, soil pH and organic matter). Sissoo volume estimates differed significantly across regions, ranging from 52.0–80.0 m 3 ha -1 in the Khulna and Chuadanga regions respectively. Our highest estimates were considerably lower than virtually all reported sissoo volume estimates due to high tree mortality in the plantations we surveyed (46.4 ± 11.3% of stems). Sissoo volume was negatively associated with soil clay content whereby the lowest region-specific rotation-age volumes associated with the highest average clay content. Results of this study suggest sissoo plantations in Bangladesh are likely to yield less revenue earnings than they have historically or compared with other commercial plantation species.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".